人工智能是对人的意识、思维的信息过程的模拟。人工智能不是人的智能，但能像人那样思考、也可能超过人的智能。
关于人工智能的英语作文优秀范文一：
Andrew Ng is hunched over his smartphone, in a pantomime of key-pecking, squinting, typo-ridden discomfort. “This is how we do it today,” he says.
吴恩达(Andrew Ng)驼着背低着头，略带夸张地在他的智能手机上比划着不停点击屏幕、眯着眼却仍然错字连篇的那种不自在的样子。“我们如今是这样做的，”他称。
“And this is how we should be doing it,” says the chief scientist for Baidu, China’s largest search engine. He sits back in his chair, speaking to no one in particular with his phone placed on the table. The one-finger typing agony of millions of smartphone users should one day become a thing of the past, he says. All it would take is the creation of a reasonably accurate, pocket-sized electronic version of a human brain.
“而我们应该这样做，”这位百度(Baidu)的首席科学家称。他靠在座位上，没有特定对象地说着话，手机放在桌子上。他说，数百万智能手机用户用一个手指敲字的痛苦有一天应该成为过去。而这只需要创造一种达到合理精确度、与口袋大小相当的电子版人类大脑。百度是中国最大的搜索引擎。
Mr Ng is an expert in deep learning, a branch of artificial intelligence that focus on teaching computers how to talk, listen, read, and think like us. The area is fast becoming a priority for the world’s biggest technology companies, including Baidu as it tackles the era of the mobile internet.
吴恩达是深度学习(deep learning)领域的专家，该领域是人工智能的一个分支，专注于让计算机学习如何像我们一样听、说、读、思。由于该领域与移动互联网时代紧密相连，它正迅速成为包括百度在内的全球最大科技公司的优先发展领域。
“The whole world is switching to mobile devices but no one has created a usable interface to input into the devices,” he says. With the development of artificial intelligence, “soon you’ll be able to order food and just say ‘Can I have some food delivered to my house before I get home?’ out loud.”
“整个世界都在转向移动设备，但是还没人创造出向移动设备输入指令的有用接口，”他称。随着人工智能的发展，“很快你将可以在订购食物时只需要大声说一句‘能在我回家前送些食物到我家中吗?’”
“It won’t even feel like technology, it will just be in the background.”
“感觉上甚至都不像是科技，而就在后台里。”
In addition to better voice recognition, AI is being talked about for any number of uses from predicting advertising clicks to recognising faces.
除了更好的语音识别，从预测广告点击量到人脸识别技术的很多领域都在讨论使用人工智能。
Since joining Baidu last year, Mr Ng has been steadily working to implement this vision. A UK native with Chinese roots, he founded in 2011 Google Brain, the US technology company’s deep learning project, and led it until he joined the Chinese company last year. Poaching him was regarded as a coup in the technology world.
自从去年加入百度以来，吴恩达一直在为实现这个愿景而稳扎稳打。作为一名出生在英国的华人，他在2011年创建了“谷歌大脑”(Google Brain)——谷歌的深度学习项目，并且在去年加入百度前一直领导着该项目。百度撬走吴恩达被认为是科技界的一次政变。
He describes the advanced computers at Baidu’s Sunnyvale, California, lab as “rocket engines” whose software can be taught to mimic the functioning of the human mind. Their “fuel” is data, which he gets from Baidu’s trove of online video and audio output as he works to teach the electronic brain to listen and speak.
他把百度位于加州森尼韦尔(Sunnyvale)实验室中的先进计算机比作“火箭引擎”，计算机中的软件可以学习模拟人类思想的功能。在吴恩达教电子大脑听和说时，它们的“燃料”就是他从百度在线视频和音频输出资料库中得到的数据。
The company has an advantage in deep-learning algorithms for speech recognition in that most video and audio in China is accompanied by text — nearly all news clips, television shows and films are close-captioned and almost all are available to Baidu and Iqiyi, its video affiliate.
百度在语音识别深度学习算法方面具有优势，因为中国大多数视频和音频都伴有文本——几乎所有新闻剪辑、电视节目及电影都有详细的字幕，而百度及其视频子公司爱奇艺(Iqiyi)可以获得几乎所有此类内容。
While a typical academic project uses 2,000 hours of audio data to train voice recognition, says Mr Ng, the troves of data available to China’s version of Google mean he is able to use 100,000 hours.
吴恩达说，一个典型的学术项目会利用2000小时的音频数据来训练语音识别，但百度——中国版谷歌——拥有的庞大数据库意味着他可以利用10万小时。
He declines to specify just how much the extra 98,000 hours improves the accuracy of his project, but insists it is vital.
他拒绝详细说明额外9.8万小时在多大程度上提升了其项目的精确度，但坚称这至关重要。
“A lot of people underestimate the difference between 95 per cent and 99 per cent accuracy. It’s not an ‘incremental’ improvement of 4 per cent; it’s the difference between using it occasionally versus using it all the time,” he says.
“许多人低估了95%精确度与99%精确度之间的区别。这不是4%的“增量”提升;这是偶尔使用与始终使用之间的区别，”他说。
Thanks to the strides made in Chinese language voice recognition — a particular challenge because of the number of homonyms and the importance of context — Baidu will soon roll out Deepspeech, a voice recognition software similar to Apple’s Siri.
由于在汉语语音识别方面取得了巨大进步(汉语中的大量同音异义词和语境的重要性使之极具挑战)，百度即将推出Deepspeech——一款类似于苹果(Apple)的Siri的语音识别软件。
Other Chinese companies including Alibaba and Tencent are also making advances in AI, but thanks largely to Mr Ng’s reputation Baidu is now judged by industry experts to be ahead of its domestic peers, ranking up alongside US rivals Facebook, Google, and IBM.
包括阿里巴巴(Alibaba)、腾讯(Tencent)在内的其他中国企业在人工智能方面也取得了进步，但主要得益于吴恩达的声望，行业专家如今认为百度要领先于国内同行，可与美国竞争对手Facebook、谷歌和IBM比肩。
“Artificial intelligence is an oligopoly,” says Yang Jing, founder of AI Era, an association for the artificial intelligence industry in China. “It’s a game for the titans.”
“人工智能是寡头垄断行业，”中国人工智能行业协会新智元(AI Era)创始人杨静说，“这是一个巨头间的游戏。”
Baidu already saves Rmb17m ($2.7m) per day at its data centres by using deep-learning algorithms to predict hard drive malfunctions, and it is also using AI to optimise the use of advertisements and photos to improve clickthrough rates. It would not reveal how much it is spending on AI development overall.
百度通过在数据中心利用深度学习算法预测硬盘故障已经可以每天节省1700万元人民币(合270万美元)，而且还利用人工智能优化广告和相片的使用来提升点击率。该公司并未透露在人工智能开发上共计投入多少资金。
But in spite of lofty long-term ambitions, translating deep learning into money-making projects is still largely on the horizon.
尽管雄心勃勃，但要将深度学习转变成赚钱的项目仍有很长一段路要走。
Mr Ng is undaunted. “There’s no question that [AI] is creating huge economic value; there’s no question that this will continue to create huge advances,” he says. “There is still a huge gap between the way machines learn and the way humans learn.”
吴恩达毫无畏惧。“毫无疑问，(人工智能)正在创造巨大的经济价值;毫无疑问，这将继续创造巨大的进步，”他说，“机器的学习方式与人类的学习方式之间仍存在巨大差距。”
关于人工智能的英语作文优秀范文二：
GWEN IFILL: Now we continue our series about artificial intelligence, A.I., where computers are able to make intelligent decisions without human input.
As computing power gets stronger and people continue to generate massive amounts of data, A.I. is making its way into the marketplace and into your doctor's examination room.
Hari Sreenivasan has the latest in series on breakthroughs in invention and innovation.
HARI SREENIVASAN: Advances in artificial intelligence continue to push the boundaries between science fiction and reality, like this brain-controlled device at the University of Minnesota. It enables users to fly a model helicopter with only their thoughts. The hope is it will soon help disabled people to operate robotic arms.
But you don't need to be in a university lab to find A.I. It's all around us.
MAN: What's the fifth planet from the sun?
HARI SREENIVASAN: Helping us search for information.
WOMAN: Jupiter is the fifth planet orbiting the sun.
HARI SREENIVASAN: Our smartphones use A.I. to navigate us, choosing the least congested traffic routes. Even the U.S. Postal Service uses it to sort mail. And on Wall Street, autonomous machines help make major financial decisions.
RAY KURZWEIL, Inventor/Futurist: At least 90 percent of the financial transactions are guided in one way or another by artificial intelligence.
HARI SREENIVASAN: Ray Kurzweil directs Google's engineering lab, but spoke to us in his capacity as an independent inventor. He's convinced that A.I. programs are already on track to solve many of the problems vexing mankind today.
RAY KURZWEIL: They're helping us find a cure for disease, helping us diagnose disease, analyzing environmental data to help us clean up the environment. Virtually every industrial process is a combination already of human and machine intelligence.
HARI SREENIVASAN: Large tech firms are betting big on the promise of A.I. Last year, Google paid $400 million to acquire DeepMind, a London startup specializing in deep learning. Facebook is raising eyebrows as it continues to pluck A.I. talent. And IBM is investing $1 billion to grow its Watson division, based out of new headquarters in New York's Silicon Alley.
Remember Watson, the supercomputer which beat a pair of “Jeopardy” game show champions in 2011?
MAN: Watson?
COMPUTER: What is Jericho?
MAN: Correct.
HARI SREENIVASAN: Well, in the four years since, IBM has sped Watson up 24-fold. What used to be a room full of computing machines can now fit into a pizza box, all accessed from the cloud.
You could say these are the brains that power Watson, but since all the data lives on the cloud, it's hard to visualize.
GURUDUTH BANAVAR, IBM: What you see is how Watson works.
HARI SREENIVASAN: Guru Banavar is vice president of cognitive computing at IBM.
GURUDUTH BANAVAR: Watson has come a very long way.
We have taken some of the underlying technologies that helped us win the “Jeopardy” game show, and applied it in many domains that matter, like health care, education, business decision-making.
HARI SREENIVASAN: Last month, IBM Introduced Watson Health, its entry into the personalized health care space. The idea is to use Watson's A.I. to make sense of vast troves of health data to deliver tailored information to physicians, insurers, researchers and hospitals.
GURUDUTH BANAVAR: The difference between any data that previously we were able to analyze and the new data that are — we have to apply artificial intelligence techniques to is that the new data is natural language. It's just written in English. Computers have never been able to understand natural language.
Typically, these are very high-end, complex information that's published by scientific researchers, and now Watson is able to read those.
HARI SREENIVASAN: At the Memorial Sloan Kettering Cancer Center, Mark Kris, a thoracic oncologist, is leading a team that is teaching Watson how to diagnose cancer.
DR. MARK G. KRIS, Memorial Sloan Kettering Cancer Center: We needed some way to help doctors deal with the deluge of information that's available now.
HARI SREENIVASAN: Watson is being trained to sort through reams of information about the patient, the most current medical research, and get it to the doctor to help make a decision, all at a pace beyond humans.
DR. MARK G. KRIS: Our kind of idea here though is that this system is going to be like what we kind of call a learned colleague.
HARI SREENIVASAN: A colleague that can assist with instant diagnoses and recommended courses of treatment. The recommendations are highly personalized based on a patient's unique genetic makeup.
DR. MARK G. KRIS: The person I'm asking about is a 55-year-old man who already has had surgery for his lung cancer. It was discovered that this cancer had spread to lymph glands that were nearby.
So, the first thing this system does is, it shows all the different treatments that are recommended. And then now I ask what kind of chemo to give, and it points to a chemo regimen, two different drugs. And if I want the more information about exactly why this decision was made, there's a little button right next to this chemo choice that takes you to the medical literature and some key publications about this regimen, the benefits it can give, and why that choice was made.
HARI SREENIVASAN: Dr. Bob Wachter is associate chair at the University of California, San Francisco, Medical School and author of a new book, “The Digital Doctor.”
DR. ROBERT WACHTER, University of California, San Francisco: In some ways, ironic that computers will probably be best at low-level tasks, pretty simple algorithmic stuff. I have a runny nose and a cough and a low-grade fever. What should I do? And high — very high-complexity stuff, like, I have an unusual form of lung cancer and I have these genetic mutations, and what should I do?
HARI SREENIVASAN: But Wachter says where computers and A.I. still struggle is in the middle.
DR. ROBERT WACHTER: A lot of medicine kind of lives in that middle ground, where it's really messy. And someone comes in to see me and they have a set of complaints and physical exam findings all that. And it could be — if you look it up in a computer, it could be some weird — it could be the Bubonic plague, but it probably is the flu.
HARI SREENIVASAN: Wachter is also concerned about fatal implications that can result from an over-reliance on computers. In his book, he writes about a teenage patient at his own hospital who barely survived after he was given 39 times the amount of antibiotics he should have received.
DR. ROBERT WACHTER: So, in two different cases, the computers threw up alerts on the computer screen that said, this is an overdose. But the alert for a 39-fold overdose and the alert for a 1 percent overdose looked exactly the same. And the doctors clicked out of it. The pharmacists clicked out of it. Why? Because they get thousands of alerts a day, and they have learned to just pay no attention to the alerts.
Where the people are relegated to being monitors of a computer system that's right most of the time, the problem is, periodically, the computer system will be wrong. And the question is, are the people still engaged or are they now asleep at the switch because the computers are so good?
HARI SREENIVASAN: That's one of many ethical questions facing scientists, and society, as artificial intelligence continues its rapid advance.
For the PBS NewsHour, I'm Hari Sreenivasan in New York.
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